Streamlining Deep Learning Network for Real-time Sea Turtle Detection by Muhamad Dwisnanto Putro, Yuliana Mose, Alex Copernikus Andaria, Jane Litouw, Vecky Canisius Poekoel, Xaverius Najoan

“…A new turtle dataset is proposed that contains lighting, blur, occlusion, and complex background challenges. The evaluation results show that the proposed model performs higher accuracy than other lightweight object detection models. …”
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A Dynamic Evaluation Method for Collaborative Search Efficiency of Multi-Sonar Systems Under Uncertain Situations by Shizhe Wang, Weiyi Chen, Zongji Li, Xu Chen

“…It discretizes the sonar search path and target motion trajectory in the time and space, and calculates the sonar detection efficiency point by point, which can overcome the challenge of uncertain situation conditions due to the uncertainty of target motion by dynamic spatial-temporal deduction. …”
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VBP-YOLO-prune: Robust apple detection under variable weather via feature-adaptive fusion and efficient YOLO pruning by Haohai You, Hao Wang, Zhanchen Wei, Chunguang Bi, Lijuan Zhang, Xuefang Li, Yingying Yin

“…These results demonstrate that VBP-YOLO-prune provides a practical and efficient solution for real-time fruit detection in complex environments. …”
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EHA-YOLOv5: An Efficient and Highly Accurate Improved YOLOv5 Model for Workshop Bearing Rail Defect Detection Application by Jiyong Hu, Hongfei Yang, Jiatang He, Dongxu Bai, Hongda Chen

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FGS-YOLOv8s-seg: A Lightweight and Efficient Instance Segmentation Model for Detecting Tomato Maturity Levels in Greenhouse Environments by Dongfang Song, Ping Liu, Yanjun Zhu, Tianyuan Li, Kun Zhang

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SAM-Based Efficient Feature Integration Network for Remote Sensing Change Detection: A Case Study on Macao Sea Reclamation by Junqing Huang, Junqi Bao, Min Xia, Xiaochen Yuan

“…To utilize the visual recognition capabilities of SAM for improving RSCD, we propose an SAM-based efficient feature integration network (EFI-SAM). Random fourier features adaptor (RFFA) is utilized to enhance Mobile SAM’s capability for extracting general features from complex RSIs, resulting in adaptive Mobile SAM, which serves as the feature extractor of EFI-SAM. …”
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Assessment of Doppler Wind Lidar Detection Efficiency and Influencing Factors at Plateau Airport: A Case Study of Lhasa Gonggar Airport by Junjie Wu, Hongyu Du, Chunjiong Xia, Xiaoyuan Huang

“…Doppler wind lidar (DWL) demonstrates significant advantages in wind field detection under clear weather conditions and has been widely applied in airports with complex wind environments. …”
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HGCS-Det: A Deep Learning-Based Solution for Localizing and Recognizing Household Garbage in Complex Scenarios by Houkui Zhou, Chang Chen, Zhongyi Xia, Qifeng Ding, Qinqin Liao, Qun Wang, Huimin Yu, Haoji Hu, Guangqun Zhang, Junguo Hu, Tao He

“…However, due to the interference of complex environments, coupled with the influence of the irregular features of garbage, garbage detection in complex scenarios still faces significant challenges. …”
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Enhancing wind turbine blade damage detection with YOLO-Wind by Zhao Zhanfang, Li Tuo

“…Furthermore, a newly added P2 detection layer enhances multi-scale defect recognition in complex environments. …”
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Efficient Switched-Beam Detection for Dynamic Spectrum Sharing in 6G Wireless Networks With Full Duplex Technology at the THz Band by Andrea Tani, Dania Marabissi

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RDRM-YOLO: A High-Accuracy and Lightweight Rice Disease Detection Model for Complex Field Environments Based on Improved YOLOv5 by Pan Li, Jitao Zhou, Huihui Sun, Jian Zeng

“…Rice leaf diseases critically threaten global rice production by reducing crop yield and quality. Efficient disease detection in complex field environments remains a persistent challenge for sustainable agriculture. …”
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Para-YOLO: An Efficient High-Parameter Low-Computation Algorithm Based on YOLO11n for Remote Sensing Object Detection by Hang Chen, Qi Cao, Yongqiang Wang, Shang Wang, Haisheng Fu, Zhenjiao Chen, Feng Liang

“…Moreover, the increasing demand for real-time onboard image processing imposes stringent requirements on both algorithmic complexity and detection accuracy. To overcome these challenges, we propose Para-YOLO, an efficient and cost-effective algorithm consisting of a novel feature fusion network and three innovative modules. …”
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Optimizing Security in IoT Ecosystems Using Hybrid Artificial Intelligence and Blockchain Models: A Scalable and Efficient Approach for Threat Detection by William Villegas-Ch, Jaime Govea, Rommel Gutierrez, Aracely Mera-Navarrete

“…Traditional security solutions, based on centralized architectures, are neither scalable nor efficient enough to handle the increasing complexity and number of IoT devices, leading to high latencies, increased energy consumption, and inadequate intrusion detection. …”
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THE EFFICIENCY OF TECHNIQUE OF DOUBLE ARCHES BY THE TREATMENT OF PATIENTS WITH ANOMALIES OF OCCLUSION by Sergei Vladimirovich Dmitrienko, Dmitry Anatolyevich Domenyuk, Anzhelika Vladimirovna Kokareva, Ernessa Grigorievna Vedeshina

“…As a result of examination and treatment of patients of the first period of mature age with various forms of occlusion anomalies it was detected an efficiency of preformed arches treatment and technique of double arches taking into account individual parameters of the dental arches on the morphometric parameters of the craniofacial complex in conjunction with the main parameters of dentoalveolar arches and individual tooth sizes. …”
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UV–Vis Detection of Thioacetamide: Balancing the Performances of a Mn(III)-Porphyrin, Gold Colloid, and Their Complex for Selecting the Most Sensitive Material by Camelia Epuran, Ion Fratilescu, Ionela Fringu, Anca Lascu, Liliana Halip, Mihaela Gherban, Eugenia Fagadar-Cosma

“…It could be concluded that Mn-3,4-diMeOPP could detect/quantify thioacetamide (TAA) in the range 3.13 × 10⁻⁸ M–7.67 × 10⁻⁷ M in a linear fashion, with a 99.85% confidence coefficient. …”
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Signal Detection for Enhanced Spatial Modulation-Based Communication: A Block Deep Neural Network Approach by Shaopeng Jin, Yuyang Peng, Fawaz AL-Hazemi, Mohammad Meraj Mirza

“…In ESM, traditional signal detection methods such as maximum likelihood (ML) have the drawback of high complexity. …”
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NavBLIP: a visual-language model for enhancing unmanned aerial vehicles navigation and object detection by Ye Li, Li Yang, Meifang Yang, Fei Yan, Tonghua Liu, Chensi Guo, Rufeng Chen

“…Additionally, these methods often fail to effectively integrate multimodal inputs, which restricts their adaptability and generalization capabilities when facing complex and diverse scenarios.MethodsTo address these challenges, we introduce NavBLIP, a novel visual-language model specifically designed to enhance UAV navigation and object detection by utilizing multimodal data. …”
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Assessing the Role of EEG Biosignal Preprocessing to Enhance Multiscale Fuzzy Entropy in Alzheimer’s Disease Detection by Pasquale Arpaia, Maria Cacciapuoti, Andrea Cataldo, Sabatina Criscuolo, Egidio De Benedetto, Antonio Masciullo, Marisa Pesola, Raissa Schiavoni

“…Quantitative electroencephalography (QEEG) has emerged as a promising tool for detecting Alzheimer’s disease (AD). Among QEEG measures, Multiscale Fuzzy Entropy (MFE) shows great potential in identifying AD-related changes in EEG complexity. …”
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Simple Single-Person Fall Detection Model Using 3D Pose Estimation Mechanisms by Jinmo Yang, R. Young Chul Kim

“…Therefore, we propose the simple fall detection model (SFDM) that is computationally efficient with moderate accuracy. …”
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A Low Complexity Near-Optimal Detector Based on Teaching-Learning Algorithm for Massive MIMO by Hamid Amiriara, Mohammadreza Zahabi

“…In this paper, a low-complexity receiver is proposed using a Teaching-Learning based optimization (TLBO) heuristic algorithm for a large-scale system. …”
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